Search Results (295)

Paeonia ostii, a significant perennial woody oil crop in China, is notable for its seeds’ high oil content and elevated levels of unsaturated fatty acids. However, there is currently a lack of scientific fertilisation protocols and targeted nutrient management for P. ostii. The concentrations of macronutrients (N, P, K, Ca, and Mg) and micronutrients (Fe, Mn, Zn, and Cu) were determined in the leaves at five distinct growth stages: flowering, initial fruit set, fruit expansion, late fruiting, and foliar senescence. The levels of N and P were found to be at their highest point during the flowering stage, after which they declined significantly. In contrast, the levels of K remained relatively stable throughout the growth phase, while Mg levels increased significantly to peak at fruit expansion. The level of Ca increased, reaching its peak at the late fruiting stage. The annual average content of micronutrients in P. ostii leaves was as follows: Fe > Mn > Zn > Cu. Furthermore, it was observed that the concentrations of Fe and Mn oscillated, while the concentration of Cu decreased significantly after flowering. Additionally, Zn concentrations remained stable throughout the various stages. Multivariate analyses, including PCA, nutrient ratio analysis, and an integrated nutrient stability index, further revealed coordinated shifts in leaf nutrient composition and indicated that May and June were relatively stable periods for nutrient assessment. Considering both the nutrient stability and the phenological relevance, June, corresponding to the fruit expansion stage, was considered a practical sampling window for foliar nutrient diagnosis. These findings contribute to the definition of an appropriate sampling window for foliar nutrient diagnosis, thereby providing a useful basis for nutrient monitoring and future fertilisation studies in P. ostii. Full article

Artificial shelterbelts in arid and semi-arid regions play a key role in controlling land degradation, regulating wind erosion, and maintaining ecological security. However, their long-term protective effectiveness increasingly depends on accurate degradation diagnosis and targeted management of aging and degraded stands. This study developed a comprehensive health assessment and degradation grading framework for poplar shelterbelts in the Kubuqi Desert, northern China, using an indicator system covering stand structure, community structure, soil conditions, health risks, and external disturbances. Indicator weights were determined using the entropy weight method, and degradation grades were classified by combining the technique for order preference by similarity to ideal solution (TOPSIS) model with the rank-sum ratio (RSR)–Probit method. The results showed that soil conditions and stand structure were the dominant dimensions distinguishing degradation status, with weights of 50.98% and 25.30%, respectively. Grade I, Grade II, Grade III, and Grade IV stands accounted for 21.88%, 25.00%, 34.38%, and 18.75% of the plots, respectively, indicating that lightly and moderately degraded stands were predominant. Degradation grades were also associated with changes in understory cover and surface soil nutrients, especially decreases in soil organic matter and alkali-hydrolyzable nitrogen. Based on these results, grade-specific management strategies were proposed, including conservation and maintenance, density regulation, assisted restoration, and near-natural transformation. This framework provides a practical basis for diagnosing degradation status and guiding the renewal and management of aging shelterbelts in arid sandy regions. Full article

Hybrid snakehead (Channa argus × Channa maculata) is a major cultured freshwater fish in China, but standardized health monitoring using serum biochemistry is limited by the lack of species-specific reference intervals. This study established reference intervals for 20 serum biochemical parameters in hybrid snakehead reared under 27 °C for 90 days. The body weights of the sampled fish ranged from 50 g to 160 g and were exempted from diseases by health check. All parameters were measured using an automated analyzer with commercial reagent kits. Most parameters exhibited non-normal, right-skewed distributions, and only total protein (TP) was normally distributed. Smoothed bootstrap resampling and kernel density estimation were applied to extract the main peak distribution and reduce bias from outliers and long tails. Species-specific reference intervals were established based on the main peak data, providing more reliable physiological baselines than conventional percentiles. Correlation analysis revealed coordinated changes among liver function, nutrient metabolism, tissue damage, and digestive enzymes. These results provide a standardized tool for health assessment, subclinical disease diagnosis, and comparative analysis in juvenile hybrid snakehead maintained at an optimal temperature in indoor mesocosm systems. Full article

Background/Objectives: Obesity, food and nutrient intake, and physical activity (PA) have been linked to the occurrence of various types of cancer. However, evidence regarding their relationship with melanoma is limited. We aimed to assess whether body mass index (BMI), diet quality, food cooking methods, and PA influence the risk of developing melanoma. Methods: This case–control study compared the demographic characteristics, dietary habits, and PA of 130 melanoma patients from the Hospital Clínic de Barcelona with 166 control subjects of similar age and sex distribution. Data was collected by means of a questionnaire, administered between January 2016 and February 2020. The association between these factors and melanoma was assessed using odds ratios for binary variables with 95% confidence intervals. Results: BMI was not found to be associated with the diagnosis of melanoma. However, restricting foods and limiting sugary products did show a correlation with lower melanoma risk, while dairy product restriction was associated with an increased risk. Consumption of processed meats and unhealthy cooking methods were also associated with an increased risk of melanoma development. Lastly, an inverse association between PA practice and frequency and melanoma risk was observed in women, while vigorous-intensity PA showed an inverse association regardless of sex. Conclusions: This study identifies specific dietary patterns and PA behaviors that may play a role in melanoma risk, highlighting the potential for personalized lifestyle-based prevention strategies. Full article

This study aimed to characterize the spatial patterns of soil nutrients and labile carbon in the 0–20 cm surface layer of a red-soil bench-terrace hillslope during the first year following cut-and-fill engineering. Soil nutrient redistribution is classically conceptualized as upslope depletion and downslope enrichment, yet whether this paradigm holds after bench terracing remains poorly documente d. On a granite-derived red-soil hillslope in Yudu County, Jiangxi Province, China, we established three replicated transects across four slope positions in May 2025, one year after cut-and-fill bench terracing combined with Camellia oleifera–Pinus massoniana mixed young-forest restoration. The 0–20 cm surface layer was sampled for pH, organic matter, total nitrogen, total phosphorus, water-soluble organic carbon, particulate organic carbon (POC), and mechanical composition. The results showed that organic matter, total nitrogen, and POC all peaked on the upper slope, with enrichment factors of 8.8×, 3.8×, and 5.1× relative to the hilltop, respectively; the slope base did not function as a nutrient sink. Texture displayed a monotonic downslope differentiation but decoupled from the nutrient gradient, and pH was significantly negatively correlated with organic matter and POC. The observed short-term post-restoration non-classical pattern is best interpreted as the spatially heterogeneous footprint of subsurface exposure and localized topsoil redistribution during cut-and-fill engineering, overlain by one year of incipient biological input, rather than the product of modified erosion–deposition dynamics. POC appears to be a particularly sensitive tracer of early biological activity under these short-term post-restoration conditions when superimposed on a depleted inverted-surface baseline, and the pronounced spatial heterogeneity implies that precision management based on high-resolution spatial diagnosis is warranted to address the substrate patchiness inherited from cut-and-fill operations. However, the temporal scope of this one-year baseline survey limits the inference of long-term indicator performance, and follow-up monitoring is needed to confirm whether POC retains this sensitivity as the surface layer matures. Full article

Background/Objectives: Phenylketonuria (PKU) is a rare autosomal recessive disorder caused by phenylalanine hydroxylase (PAH) deficiency, impairing the conversion of phenylalanine (Phe) to tyrosine. Although early diagnosis and intervention yield excellent outcomes, dietary adherence often declines in adulthood, potentially leading to poor metabolic control and adverse nutritional consequences. This study aimed to evaluate physical activity levels, nutritional status, metabolic control, and anthropometric outcomes in adults with classic PKU, which have not been sufficiently researched in the current literature. Methods: This cross-sectional study included 100 adults with classical PKU (cPKU; baseline phenylalanine levels ≥ 1200 µmol/L) under regular follow-up at the Division of Metabolism, Hacettepe İhsan Doğramacı Childrens’ Hospital. Sociodemographic traits and dietary behaviors were evaluated through structured interviews carried out by a dietitian. Dietary intake was assessed by using a 24 h dietary recall method, and nutrient analyses were performed with the Bebis 7.2 software program. Using the short version of the International Physical Activity Questionnaire (IPAQ), physical activity levels were specified, and participants were categorized according to established scoring criteria. Results: A hundred adults with classical PKU took part in the study, including 47 males and 53 females, with a mean age of 23.84 ± 5.41 years; 5% of participants were underweight, 40% had normal weight, 39% were overweight, and 16% were listed as obese. The intake of mean daily energy is 2443.8 ± 384.6 kcal for men and 1822.5 ± 312.7 kcal for women. Carbohydrates contributed approximately 61% of total daily energy intake in both genders, whereas protein accounted for 12–13% and fat for approximately 26–27% of total energy intake; 17% of participants were physically inactive, 40% were minimally active, and 43% met criteria for sufficient physical activity according to IPAQ-based classification. Energy intake, the use of Phe-free protein substitutes, and BMI were significantly higher in the sufficiently active group compared to the low-active group in men, while no significant differences were observed between physical activity groups among women. Conclusions: Adults with classical PKU showed a high prevalence of overweight and obesity, together with differences in dietary intake and physical activity patterns. Physical activity levels were associated with several nutritional and metabolic characteristics; however, further long-term research is required to fully understand these connections. Full article

Urban reservoirs are increasingly exposed to multiple interacting pressures associated with eutrophication, pollutant inflow, ageing sewerage and stormwater infrastructure, and climate-related hydrological instability. This issue is of growing concern because municipalities often possess fragmented monitoring and planning evidence without an operational framework for translating it into remediation action. This study develops an integrated decision-support framework for the Ternopil Reservoir based primarily on recent hydrochemical monitoring data, complemented by historical targeted sampling and local environmental and planning materials. The analysis focuses on the most informative indicators of ecological deterioration in an urban reservoir, including oxygen regime, organic pollution, nutrient-related parameters, suspended solids, and selected pollution markers. The available evidence indicates that the Ternopil Reservoir is among the most environmentally stressed water bodies within the local reservoir system, with recurrent eutrophication symptoms, seasonal water blooming, and spatially differentiated exceedances of selected water-quality indicators. The results further indicate persistent nutrient-related and organic pressure, pronounced hydrochemical tension in 2022, and hotspot vulnerability in hydraulically weak sectors of the reservoir. To address these pressures, the study proposes a four-stage monitoring-to-remediation framework that links environmental diagnosis with the identification of vulnerable zones, the prioritisation of hydraulic and hydrobiological measures, and post-remediation control. The proposed framework is intended as an operational planning tool for translating fragmented local evidence into a coherent remediation pathway for urban reservoirs under multiple environmental stressors. Full article

Cyanobacterial harmful algal blooms are an increasing concern for wildlife health, particularly in eutrophic wetlands, yet well-documented avian cases supported by environmental, pathological, and toxicological evidence remain scarce. This study describes a sentinel case of probable microcystin toxicosis in a Red-gartered coot (Fulica armillata) from Laguna Petrel, a protected coastal wetland in central Chile, during a broader wildlife mortality event. Surface-water monitoring included nutrient analyses, in situ physicochemical measurements, phytoplankton assessment, and cyanotoxin quantification. The evaluated bird was documented alive with severe motor impairment, euthanized, and examined by gross necropsy, histopathology, and tissue toxicology. Water analyses showed elevated nutrients, persistently alkaline and highly productive conditions, marked dominance of Microcystis aeruginosa, and high concentrations of microcystin-LR, microcystin-RR, microcystin-YR, and nodularin. The bird showed marked hepatic lesions at necropsy, histopathological changes compatible with acute hepatotoxic injury, and detectable microcystin-LR in lyophilized liver tissue. Taken together, these findings support a diagnosis of probable microcystin toxicosis in this individual. This case highlights the value of waterfowl as sentinels of ecosystem health threats and underscores the importance of integrated monitoring in protected coastal wetlands potentially affected by toxic cyanobacterial blooms. Full article

Nitrogen (N) management is critical for optimizing growth and fruit quality in open-field strawberry cultivation, demanding advanced technological solutions for reliable nutrient assessment. However, visual symptom diagnosis, though widely utilized for nutrient monitoring, is inherently subjective and prone to observer bias, resulting in inconsistent and often unreliable assessments. While available accurate tissue analysis is destructive and costly. Nondestructive, in-field imaging techniques such as the normalized difference vegetation index (NDVI) exist but require expensive multispectral imaging systems. To address these limitations, this study developed a streamlined methodology for in-field N status detection using deep learning on standard RGB images. The experiment utilized ‘Yotsuboshi’ strawberries in a randomized complete block design with sufficient nitrogen (T1) and deficient nitrogen (T2) treatments. To mitigate ambient light variability, a key challenge in open-field phenotyping, a low-cost phenotyping cylinder was developed for standardized smartphone image acquisition. Rigorous four-stage annotation criteria were also introduced to classify the nitrogen status in strawberry leaves as NormalN, LowN, or AdvancedLowN, ensuring a high-quality novel dataset. A YOLO11 model trained on this dataset achieved precision, recall, and mAP50 values exceeding 99%. Subsequent testing using the phenotyping cylinder yielded a mAP50 of 87%. In-field validation without a phenotyping cylinder also demonstrated robust performance under diffuse cloudy conditions (82.7% mAP50), outperforming direct sunlight (79% mAP50). Moreover, the model’s classifications of ‘NormalN’ and ‘LowN’ statuses strongly corresponded with NDVI measurements, validating the accuracy of the RGB-based approach. This research demonstrates the significant potential of combining deep learning and phenotyping cylinder to create a rapid, low-cost, nondestructive and reliable tool for in-field nitrogen detection, with possible application across different crops and environmental conditions. Full article

Tomato (Solanum lycopersicum L.) production faces increasing pressure from resource scarcity and climate change, creating demand for more precise and adaptive management. However, adoption in commercial systems remains limited because many advanced technologies are costly, poorly interoperable, or difficult for growers to interpret. This review addresses that gap by organizing recent advances into a five-stage production ecosystem framework: Measurement, Understanding, Optimization, Prediction, and Diagnosis. Unlike previous precision agriculture reviews that mainly summarize sensing, modeling, artificial intelligence, and robotics as separate topics, this framework emphasizes stage-linked integration and decision support relevance across practical tomato production. Measurement establishes the data foundation through sensor networks and imaging; Understanding converts observations into physiological insight using process-based models; Optimization applies these insights to water, nutrient, and microclimate management. Prediction uses machine learning and explainable artificial intelligence to anticipate yield, quality, and stress responses, while Diagnosis supports timely disease detection and vision-based intervention. Overall, this review shows that progress in tomato precision agriculture depends less on isolated algorithmic advances than on cost-effective, modular, interpretable, and operationally feasible systems for commercial deployment. Full article

Microorganisms can aggregate and organise into structured communities embedded within an exopolysaccharide-based matrsix, which serves as a protective barrier and a functional environment around microbial cells. The formation of biofilms is widely recognised as a pivotal factor in bacterial virulence, impeding the efficacy of antimicrobial agents and hindering immune responses, whilst concomitantly contributing to the development of antimicrobial resistance and the onset of persistent infections. Biofilm formation is a tightly regulated and dynamic process, controlled by quorum-sensing mechanisms and profoundly influenced by environmental factors and nutrient availability. The objective of this review is to elucidate the significance of biofilms in clinical settings, with a particular focus on their role in the pathogenesis of infectious diseases. Particular attention is devoted to biofilm-associated infections and infections related to invasive medical devices, with a particular emphasis on the most prevalent microbial pathogens, which include S. aureus, S. epidermidis, P. aeruginosa, E. coli, K. pneumoniae, A. baumannii and various species of Candida. Furthermore, the present review encompasses biofilm-associated chronic infections, conditions manifesting in predisposed patients, including individuals affected by cystic fibrosis. This review further examines the most recent strategies for combating antibiotic resistance in bacterial biofilms. This review focuses on recent biofilm pathogenesis advancements, with a focus on diagnosis challenges and the need for new ways to disrupt biofilm integrity. Full article

Improving crop yields while reducing environmental impacts remains a major challenge for smallholder agriculture, where heterogeneous management practices often limit the performance of technologies. This study developed a Select–Analyze–Design–Evaluate (SADE) framework to enhance the effectiveness of sustainable winter wheat technologies in smallholder farming systems. The framework was implemented in two villages on the North China Plain during a four-year field-based study (2017–2021), combining farmer follow-up surveys with field trials. During the Select stage, baseline data identified widely adopted technologies with substantial performance variability. Accordingly, delayed nitrogen application in Nanxia Village and precision seeding in Wangzhuang Village were selected as priority technologies for targeted diagnosis and improvement. During the Analyze stage, regression models identified key agronomic constraints: nutrient management in Nanxia, and sowing date and nitrogen management in Wangzhuang. Following this diagnosis, village-specific strategies were designed, implemented, and evaluated through multi-stakeholder collaboration. In Nanxia, yield, benefit–cost ratio, and nitrogen recovery efficiency increased by 7.9%, 21.5%, and 23.5%, respectively, while greenhouse gas emissions decreased by 21.5%. In Wangzhuang, the corresponding changes were 11.2%, 48.7%, 45.7%, and −22.9%, respectively. These findings demonstrate that SADE offers a practical pathway for sustainable smallholder agriculture. Full article

Silicon is increasingly applied in agriculture to improve plant productivity under both abiotic and biotic stress constraints. Nevertheless, its mechanisms of action are often studied separately at the soil, plant, or microbiome levels, limiting a comprehensive understanding of its overall impact on agroecosystem functioning. This review proposes an integrated perspective of the soil–plant–microbiome continuum, linking silicon chemistry in soil solutions with the effects of silicon amendments on soil properties and the processes of uptake, transport, and deposition in the plants. We show that silicon bioavailability depends on maintaining a pool of dissolved silicon dominated by orthosilicic acid, regulated by mineral weathering, adsorption–desorption dynamics, polymerization, pH, iron and aluminum oxides, and organic matter. In soils, silicon inputs can improve structure, modulate acidity and cation exchange balances, influence nutrient availability, and reduce the mobility of certain metals. They may also affect enzymatic activities and microbial community composition. In plants, silicon uptake and transport, mediated by specific transporters, contribute to tissue silicification, the maintenance of leaf architecture, and the regulation of water, ionic, and redox homeostasis. These processes provide a basis for enhanced tolerance to drought, salinity, and metal toxicity, as well as biotic stress caused by pathogens and pests. Finally, we discuss key limitations to the agronomic application of silicon, including the diagnosis of the silicic status of soils, the choice of source and mode of application, and the genotypic variability of acquisition, as well as the need for multi-site tests and more robust mechanistic validations. This synthesis provides a coherent mechanistic framework to better define the conditions under which silicon can serve as a reliable tool for sustainable crop management under climate change. Full article

Background/Objectives: Dietary patterns may influence depression, yet findings remain inconsistent, partly due to methodological variation in dietary pattern identification. As data-driven approaches may help reduce subjectivity and improve reproducibility in dietary pattern identification, this study aimed to identify dietary patterns using a machine learning approach and examine their associations with depression among Korean adults. Methods: Using data from 21,321 Korean adults aged 19–64 years from the Korea National Health and Nutrition Examination Survey (2016–2021), we applied K-means clustering to identify dietary patterns based on both food group and nutrient intake. Dietary intake was assessed using a 24 h dietary recall, and depression status was based on physician diagnosis. Results: Three distinct patterns were identified in both food group-based and nutrient-based analyses. In the food group-based analysis, a balanced and diverse dietary pattern (Cluster 3) was associated with lower odds of depression compared with a pattern characterized by overall low food intake (Cluster 1) (OR 0.64; 95% CI, 0.47–0.88; p = 0.007) after full adjustment, whereas no significant association was observed for the high processed food pattern (Cluster 2 vs. Cluster 1) (OR 0.73; 95% CI, 0.53–1.01). No significant associations were observed for nutrient-based clusters after full adjustment. Conclusions: Our findings suggest that adherence to balanced and diverse dietary patterns based on whole foods is associated with lower odds of depression. Food group-based clustering approaches may offer more reproducible and interpretable insights than nutrient-based approaches, supporting their potential utility in epidemiological research and public health strategies. Full article

Accurately identifying medium- and low-yield farmlands (MLYF) and diagnosing their constraints are essential for targeted improvement of productivity and national food security. However, traditional evaluation is usually limited by coarse spatial resolution and high labor costs, and a methodological gap remains between large-scale MLYF classification and system constraints diagnosis. To address the current methodological gaps, this study developed a comprehensive framework to determine the spatial distribution of MLYF in northern China and clarify their key constraints. The framework combined the Spatio-Temporal Random Forest (STRF) algorithm with vegetation indices (VIs), climate, and soil data to delineate MLYF and uses interpretable machine learning to diagnose major constraints. The model showed high explanatory power and ensured the reliability of attribution results. The results showed that MLYF exhibited obvious spatial heterogeneity, accounting for 48.66% of the total cultivated land in the study area. These MLYF are primarily concentrated in the northwestern Loess Plateau (LP), the central Along the Great Wall (ATGW) region, and the peripheries of the Huang-Huai-Hai (HHH) Plain. In addition to spatial classification, our analysis revealed significant differences in constraint mechanisms: soil structural, nutrient, and salinization constraints predominantly restrict productivity in the HHH Plain, whereas water stress and soil erosion are the primary drivers of yield gaps in the LP and ATGW regions. These findings provide new data and insights for understanding the spatial heterogeneity of farmland quality in typical dryland agricultural regions in northern China, and offer a scientific basis for targeted land improvement and regional agricultural sustainability. Full article